Adaptive market hypothesis and evolving predictability of bitcoin
By S. Khuntia, J. K. Pattanayak. Economics Letters, 2018
202 citations recorded by the source corpus.
This study evaluates the adaptive market hypothesis (AMH) and evolving return predictability in bitcoin market. We use two robust methods in a rolling-window framework to capture time-varying linear and nonlinear dependence in bitcoin returns. We find that market efficiency evolves with time and validates the AMH in bitcoin market.
Subfields: Economics and Econometrics, Information Systems
View Paper: https://www.semanticscholar.org/paper/0a7dc72b8e07e2622b47ecfedd9693ccfd0ba3dc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Emmanouil Platanakis
- M. Gronwald
- Andrew Urquhart
- Charles M. S. Sutcliffe
- David Martínez-Rego
- Carmine Ventre
- Leslie Kanthan
- Lingbo Li
In Information Systems
- Emmanouil Platanakis
- M. Gronwald
- Andrew Urquhart
- Charles M. S. Sutcliffe
- David Martínez-Rego
- Carmine Ventre
- Leslie Kanthan
- Lingbo Li
Citations in the corpus
- Is Bitcoin a Commodity? On price jumps, demand shocks, and certainty of supply (2019, background): “Sanches (2018) and Kumhof and Noone (2018) are mainly concerned about effects on bank funding, credit and liquidity provision, and crowding out of bank deposits.”
- Cryptocurrency trading: a comprehensive survey (2020, methodology): “[136] applied the adaptive market hypothesis (AMH) in the predictability of Bitcoin evolving returns.”
- Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks (2020, unknown): “The literature on cryptocurrencies is growing, with many papers reporting the inefficiency of Bitcoin (Urquhart 2016; Khuntia and Pattanayak 2018; Nadarajah and Chu 2018; Tiwari et al 2018), the hedging and diversification benefits (Bouri et al 2017; Corbet et al 2018a; Urquhart and Zhang 2018;…”
- Is non-fungible token pricing driven by cryptocurrencies? (2021, unknown): “The study at a more general level contributes to understanding of how pricing behaviour develops in new markets (Khuntia and Pattanayak, 2018).”
- Optimal vs naïve diversification in cryptocurrencies (2018, background): “…in Bitcoin (Cheah and Fry 2015; Corbet et al 2017), the market efficiency of Bitcoin (Urquhart 2016; Nadarajah and Chu 2017; Tiwari et al 2017; Khuntia and Pattanayak 2018), the hedging and diversification benefits of Bitcoin (Bouri et al 2017a; Corbet et al 2018a), the unique features of…”